Journal of the Korea Convergence Society (한국융합학회논문지)

Korea Convergence Society (한국융합학회)
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Construction of Super-Resolution Convolutional Neural Network Model for Super-Resolution of Temperature Data

기온 데이터 초해상화를 위한 Super-Resolution Convolutional Neural Network 모델 구축

  • Kim, Yong-Hoon (Department of Computer Science, Kwangwoon University) ;
  • Im, Hyo-Hyuk (Korea Oceanic & Atmospheric System Technology) ;
  • Ha, Ji-Hun (IT Division, Korea Oceanic & Atmospheric System Technology) ;
  • Park, Kun-Woo (IT Division, Korea Oceanic & Atmospheric System Technology) ;
  • Kim, Yong-Hyuk (Department of Computer Science, Kwangwoon University)
  • 김용훈 (광운대학교 컴퓨터과학과) ;
  • 임효혁 ((주)한국해양기상기술) ;
  • 하지훈 ((주)한국해양기상기술 IT본부) ;
  • 박건우 ((주)한국해양기상기술 IT본부) ;
  • 김용혁 (광운대학교 컴퓨터과학과)
  • Received : 2020.05.11
  • Accepted : 2020.08.20
  • Published : 2020.08.28
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Abstract

Meteorology and climate are closely related to human life. By using high-resolution weather data, services that are useful for real-life are available, and the need to produce high-resolution weather data is increasing. We propose a method for super-resolution temperature data using SRCNN. To evaluate the super-resolution temperature data, the temperature for a non-observation point is obtained by using the inverse distance weighting method, and the super-resolution temperature data using interpolation is compared with the super-resolution temperature data using SRCNN. We construct an SRCNN model suitable for super-resolution of temperature data and perform super-resolution of temperature data. As a result, the prediction performance of the super-resolution temperature data using SRCNN was about 10.8% higher than that using interpolation.

기상과 기후는 인간의 생활과 밀접하게 연관되어 있다. 특히 고해상도 기상 데이터를 활용하여 정밀한 연구나 실생활에 유용한 서비스가 가능하므로, 고해상도 기상·기후 데이터를 생산해야할 필요성이 증가하고 있다. 기존의 고해상도 기상 데이터는 적절한 보간법에 따라 데이터를 생산하지만, 본 논문에서는 SRCNN을 이용하여 기온 데이터를 초해상화 하는 방안을 제안한다. 기온 데이터 초해상화에 가장 적절한 SRCNN 모델을 구축하고, 기온 데이터를 초해상화 한다. 결과 데이터를 평가하기 위해 역거리 가중법을 이용하여 비 관측 지점에 대한 기온을 구하고, 제안한 방법을 적용한 기온 데이터와 보간법을 이용한 기온 데이터를 비교한다. 비교 결과, 기온 데이터를 초해상화하기 위한 적절한 SRCNN 모델을 구축하였고, 제안한 방법이 보간법을 이용한 방법보다 약 10.8% 더 높은 예측 성능을 보였다.

Keywords

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